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datadog-mcp-server

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aggregate-ci-tests

Aggregate and compute statistics on CI test data with grouping by fields like service or status.

Instructions

Aggregate CI test data with statistical computations and grouping

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryNoCI test search query for aggregation*
fromYesStart time (ISO 8601 or relative)
toYesEnd time (ISO 8601 or relative)
aggregationYesAggregation type
metricNoMetric to aggregate on. Example: @duration
groupByNoField to group results by. Example: @test.service, @test.status
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are present, so the description must disclose behavioral traits. It mentions 'statistical computations and grouping' but does not clarify if the operation is read-only, destructive, or requires specific permissions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single concise sentence with no wasted words. It is front-loaded with the key action, though it could benefit from slight expansion on usage.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description does not explain the output format or behavior. With no output schema, the agent lacks information about return values, pagination, or error handling, making the definition incomplete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the input schema already documents all parameters. The description does not add additional meaning or context beyond the schema descriptions, resulting in baseline score.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'aggregate', resource 'CI test data', and the type of operation 'statistical computations and grouping'. It distinguishes from sibling tools like 'search-ci-tests' and 'aggregate-ci-pipelines'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives (e.g., search-ci-tests or aggregate-ci-pipelines). The description lacks any context about prerequisites or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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